Abstract

In this paper, we investigated the effectiveness of price limit on stock market with the correlation study and complex network technology. We proposed a time-migrated DCCA cross-correlation coefficient which is beneficial to detect the asynchronous correlations of nonstationary time series. The stock market network is constructed with the threshold method based on time-migrated DCCA. The effectiveness of the price limit during the stock market crash period is studied based on the time-migrated DCCA stock market network. The results indicate that the time-migrated DCCA ensures more relevant results than the equal-time DCCA method. An interesting finding is that the price limit has different effects on the stock market network at different stages of dynamic evolution. Market stabilization will be lowered and the systemic risk will be increased if the price limit is enhanced. Such studies are relevant for a better understanding of the stock market and have a significant contribution to the stock market in reality.